An equation was created for the line of best fit from enrollment data. It was used to predict the dance studio enrollment values shown in the table below:

enrollment month January February March April may june. Actual 500 400 550 550 750 400.

Predicted 410 450 650 650 600 450.

Residual 90 -50 -100 -100 -150 -50.

Analyze the data determine wether the equation that produced the predicted values represents a good line of best fit

1) No, the equation is not a good fit because the sum of the residuals is a large number
2)No, the equation is not a good fit because the residuals are all far from zero
3)Yes, the equation is a good fit because the residuals are not all far from zero
4)Yes, the equation is a good fit because the sum of the residuals is a small number

is this part of a question or something

so firstly, we need to isolate the y variables to be able to solve these inequalities. firstly, add 0.5x on both sides of the first inequality and subtract 1.5x on both sides of the second inequality:

now since the slope is positive for the first inequality, this means that the line going upwards belongs to the first inequality, and the line going downwards belongs to the second inequality.

next, since y ≥ in the first inequality, this means that the shaded region will be above the first inequality's line, thus shading regions a and b.

next, since y ≤ in the second inequality, this means that the shaded region is going to be below this line, thus shading regions a and c.

since both lines shade region a, this means that region a is the solution.

step-by-step explanation:

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step-by-step explanation: